The effect of inter-temporal demand interactions on joint pricing and inventory ordering

In most joint pricing and production planning/inventory ordering models, demand or distribution of demand is either known or induced by pricing decisions in the period that the demand is experienced. However, empirical studies of pricing data have shown that consumers make purchasing decisions by considering prices not only in the current period, but also in past and future periods.; In this thesis, we develop two classes of models that explicitly capture the effects of inter-temporal demand interactions on optimal pricing and manufacturing decisions. First, we analyze a deterministic discrete-time finite-horizon pricing and production problem where demand at each period depends on current and past pricing decisions. We formulate the problem as a mathematical programming model and develop solution techniques. We identify structural properties of the model and develop closed-form solutions and effective heuristics for various special cases. Next, we consider the joint pricing and inventory control problem for a single product system facing demand in each period that is a stochastic function of the current price as well as prices in previous periods. We formulate this problem as a stochastic dynamic programming model and characterize the structure of optimal joint pricing and inventory ordering policy. Finally, for both sets of models, we conduct extensive computational studies in order to illustrate the effect of various cost and demand parameters on optimal pricing and inventory ordering decisions.